AI Competencies are Essential for Product and Technology Companies: Faircent

Shakti Goel, Chief Product and Technology Officer, Fairassets Technologies, better known as Faircent, India’s leading peer-to-peer lending platform, spoke to Amit Singh on the company’s digital transformation journey, how AI enabled it to excel in the market place, and how the company gathered competencies around AI

Please take us through your digital transformation journey

I joined Faircent around two years ago. When I joined as the chief of product and technology, everything was being done using Excel. We didn’t have any application as well as ERP. However, over the last 2 years, we have gone from 100 percent Excel to zero percent Excel. What that means is that everything is done online, everything is automated. We have introduced intelligent automation; we have used AI strategies to engage customers. When I joined the company, there was only one person in the operations team and after two years the business has grown several-fold but there is still single person in the operations team. That’s the measure of success of the digital transformation in our business.

We have implemented AI solutions only recently. The reason is that first we had to wait for critical volume of the data to be collected. Once we had the data collected we were able to analyze it and one the data is analyzed we were able to develop strategies and feed the information back into the system. Here I give you an example, we know who the good borrower is, and we know the parameters of the good borrower who will pay his EMIs on time. So when a new lead comes in we automatically enforce our AI engine on the data of the new lead. And we are able to predict with the certain degree of confidence whether this person is going to default or not.

For example, our AI is able to predict at 84 percent success rate of whether a loan is not going to default. So slowly overtime once we have the entire system digitized, we have collected large volume of data, and we are now able to implement the AI system.

There is a large crunch on skills and expertise on AI. What is your strategy to build competencies and solutions on AI?

AI solution has three main components: mathematical algorithm such as neural network, Random Forest, linear regression, and clustering so you need to have skills around that. The solution should be able to ingest large volume of data coming to you at high velocity. Thirdly, combining the two and using the technology such as Hadoop which can work on large volumes of data to implement the AI solution. Now, the way we do that is it will be very costly to build this expertise in-house from day one. So there are specialist companies who actually have a predefined and pre-built AI solutions and we just need to plug and play into our systems.

However, over the time if you are a product and technology company and need to rely heavily on AI intelligence then it is advisable that the company builds a team of data scientists and these data scientists have to be entrepreneur in their nature in the sense that whatever they do they need to do in terms of marketing and business perspective.

How do you zero in on the right set of solution providers?

The main strategy that we follow is to look for partners who have worked in our space. Our space is Fintech, hence the solution provider must have worked in the financial space both in retail in loan origination as well as investment banking. The company should have expertise in our domain, then we also look at the pedigree of the company in terms of where are the employees coming from, the universities, educational background and we look for recommendations of their existing clients. Finally, when we choose the partner, we make sure that the partner has skin in the game. It means that the partner gets paid if the partner has made the success story.